Representative color designating method using reliability

ABSTRACT

A method for designating a representative color which is expressed based on a reliability that a representative color of an image region expresses an image region is disclosed. This method includes a step for expressing a reliability of the representative color value as a color information of the image region together with a representative color value which represents the image region in a method using a color value as an information with respect to an image region, for thereby expressing a color information of an image region using a reliability and a color segmentation method of an image region.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a representative color valuedesignating method for an image search system, and in particular to amethod for designating a representative color of an image region byexpressing a representative color value with respect to an image regiontogether with a reliability which represents an accuracy of therepresentative color, and to a method for measuring a similarity of morethan two images and a method for segmenting an image into similarregions using a feature of a representative color value expressedtogether with the reliability.

2. Description of the Background Art

In an image search technique, a color information used for an imagesearch is an important factor in the characteristic of images.

In a conventional art, there is a method in which an image is segmentedinto a n×m number of grids, and a color histogram is obtained withrespect to each segmented cell, and a maximum value of the thuslyobtained color histogram is determined as a representative color valuewith respect to a corresponding cell. In another method, an averagevalue of the color histogram is determined as a representative colorvalue of a corresponding cell. In another method, a major color vectoris obtained and determined as a representative color value for acorresponding cell.

However, since the characteristics of the images are various, it isdifficult to express an image using a color in an image region or onecolor value. It is improper to express a feature of an image byexpressing the image region using one representative color valueinformation. In this case, it is difficult to form an accurate databaseusing the characteristics of images, and the performance of an imagesearch using the thusly formed database is decreased. Furthermore, whenexpressing a representative color of an image region using variouscolors instead of one color, a large storing space is required. Inaddition, it is difficult to accurately express an interrelationshipbetween various colors. Therefore, a representative color value of thethusly determined image region has a low accuracy.

SUMMARY OF THE INVENTION

Accordingly, it is an object of the present invention to provide amethod for designating a representative color which is expressed basedon a reliability that a representative color of an image regionexpresses an image region.

It is another object of the present invention to provide a method forexpressing a color information of an image region using a reliabilityand a color segmentation method of an image region.

It is still another object of the present invention to provide arepresentative color designating method which may be used for an imagesearch based on a weight in accordance with a reliability.

To achieve the above objects, there is provided a representative colordesignating method which comprises a step for expressing a reliabilityof the representative color value as a color information of the imageregion together with a representative color value which represents theimage region in a method using a color value as an information withrespect to an image region.

Additional advantages, objects and features of the invention will becomemore apparent from the description which follows.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become more fully understood from thedetailed description given hereinbelow and the accompanying drawingswhich are given by way of illustration only, and thus are not limitativeof the present invention, and wherein:

FIG. 1 is a flow chart of a representative color designating methodusing a reliability according to the present invention;

FIG. 2 is a flow chart of a method for obtaining a reliability using acolor similarity according to the present invention;

FIG. 3 is a flow chart of a method for obtaining a color similarityaccording to the present invention;

FIG. 4 is a flow chart of a method for obtaining a reliability using amixed rate and color similarity according to the present invention;

FIG. 5 is a flow chart of a method for obtaining a mixed rate accordingto the present invention;

FIG. 6 is a flow chart of a method for obtaining a frequency of a colorpixel which has a chrominance exceeding a certain threshold value in animage region according to the present invention;

FIGS. 7 and 8 are views illustrating an example of a method forsearching a presence of a corresponding color by adapting an expansionmask to an image region for thereby obtaining a mixed rate according tothe present invention;

FIG. 9 is a flow chart of a method for designating a representativecolor value using a reliability according to the present invention;

FIG. 10 is a flow chart of a method for designating a representativecolor value using a reliability in an image region according to thepresent invention;

FIG. 11 is a view illustrating a result(data structure) of arepresentative color designation of an image region expressed togetherwith a reliability according to the present invention;

FIG. 12 is a flow chart of a method for setting a representative colorvalue and a reliability of each cell of a grid of an image regionaccording to the present invention;

FIG. 13 is a flow chart of a method for obtaining a color similaritybetween two image grids with respect to two regions according to thepresent invention;

FIG. 14 is a view of a result of a representative color designation ofan image region which is expressed by a reliability together with arepresentative color value having a certain degree reliability accordingto the present invention; and

FIG. 15 is a flow chart of a method for obtaining a similarity region inwhich an image region is properly segmented using a reliabilityaccording to the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is directed to a method for designating arepresentative color of an image color based on a reliability that arepresentative color accurately expresses an image region whendesignating a representative color with respect to a certain imageregion. In addition, the present invention is directed to a method fordetermining a reliability in accordance with a mixed rate and colorsimilarity of colors of an image region.

In addition, the present invention is directed to a method for obtaininga similarity between images by comparing a representative color andreliability of each cell with respect to more than two image regions byobtaining a representative color and reliability with respect to eachgrid cell after segmenting an image region into multiple grids.

Furthermore, the present invention is directed to a color segmentationmethod for segmenting an image into regions having the same color inaccordance with a reliability degree by expressing a representativecolor and reliability of an image region.

The embodiments of the present invention will be explained withreference to the accompanying drawings.

FIG. 1 is a flow chart of a representative color designating methodusing a reliability which includes a step for obtaining a reliability ofan image region, a step for setting the thusly obtained reliability withrespect to the image region as a reliability of the above-describedregion, and a step for setting a representative color value of the imageregion together with the reliability.

In the present invention, the reliability is an information representingan accuracy of a color value representing a certain region for an entireimage or a certain portion within the image and is a value on whether acertain region expresses one color and is an accuracy when acorresponding region is expressed by the color and has a value between 0and 1.

Therefore, assuming that the image region is formed of one color and thecolor is designated as a representative color of the region, thereliability of the representative color is 1. While, if the image regionconsists of different clear colors and one color among the differentclear colors is designated as a representative color, the reliabilitybecomes 0.

In addition, even when an image is formed of various colors, if thecolors are properly mixed, the colors may be seen like one color. Forexample, blue colors and red colors are properly mixed in an imageregion, the thusly mixed colors may be seen like a purple color. Evenwhen the colors are nor properly mixed, in this case, when an image isformed of similar colors, one color among the above-described colors maybe designated as a representative color. When the thusly designatedrepresentative color may represent the image, the reliability withrespect to the representative color is enhanced. For example, even whenvarious yellow color groups are not properly mixed, a certain yellowcolor group may be designated as a representative color.

Therefore, in the present invention, the reliability is set based on avalue which is determined in accordance with the mixed rate and colorsimilarity of the colors in the image region. The method for obtainingthe reliability will be explained later with reference to FIGS. 2through 8. When expressing the representative color value of the imageregion with the reliability, the representative color value may be usedfor searching the images based on the weights. In addition, it ispossible to perform a color segmentation using the reliability. Thedescription thereon will be provided later with reference to FIGS. 11through 15.

Two methods are disclosed for obtaining a reliability in the presentinvention. One method is directed to removing a mixed element based onan averaging process of the image region and obtaining a reliability inaccordance with the color similarity. The other method is directed toobtaining an accurate value of the mixed rate and obtaining areliability based on the color similarity.

The first embodiment of the present invention for obtaining areliability of the image region will be explained with reference toFIGS. 2 and 3. The mixed element is removed by the averaging process ofthe image region, and then the reliability is obtained based on thecolor similarity.

In the embodiments of the present invention, the image region is assumedas a rectangular region. Otherwise, the above-described methods possiblybe adapted by considering the boundary portion.

The image region is changed to an image having a lower resolution. Atthis time, an average value of the n×n square pixel color values isobtained, and the n×n square pixels are changed to one pixel having anaverage color value, or the image region is filtered using the n×naverage filter to obtain the same result. In the earlier method, errorsoccur, but the processing speed is fast. In the later method, the valuesare accurate but the processing speed is slow.

When performing the averaging process, the number of colors existing inthe image region is decreased after the averaging process, so that anyeffects of the mixed elements are removed.

In the first embodiment of the present invention, the color similarityC-Sim is obtained after the averaging process is performed, and thethusly obtained value is set as a reliability value of the image region,and then the reliability is obtained.

The method for obtaining the color similarity C-Sim will be explainedwith reference to FIG. 3.

First, an average color value is obtained with respect to all pixels ofthe image region. A hue(Hue_av), light(L_av), chrominance(Ch_av) areobtained with respect to the average color. In addition, all colorpixels of the image region are changed to hue, light, chrominanceelements, and then the average of the hue, light, chrominance elementsis obtained. In this case, a result thereof is same.

The hue, light, chrominance elements with respect to the average colorof the image region are obtained, and then the color of each pixel ischanged into hue(H_i), light(L_i), chrominance(Ch_i) elements withrespect to each pixel Pi of all pixels, and the distance(hereinaftercolor difference) in a color coordinate space is obtained between thevalues (H_i, L_i, Ch_i) and the average values (H_av, L_av, Ch_av), andthe color differences are summed up to the last pixel.

The thusly summed color difference becomes sum of all the colordifference value between each pixel and an average color. The summedcolor difference value is normalized to 0 through 1, and a result valueobtained by subtracting the normalized value from 1 becomes a colorsimilarity C_Sim.

In the first embodiment of the present invention, the thusly obtainedcolor similarity value C-Sim is the reliability. Here, any colorcoordinate spaces which is used for obtaining the color similarity C-Simmay be available. As the color coordinate space is uniformly changedalong with the human color perception, the value obtained based on thecolor coordinate space becomes a relatively accurate value.

Next, the second embodiment of the present invention for obtaining areliability will be explained with reference to FIGS. 4 through 6. Inthe second embodiment of the present invention, an accurate value of themixed rate is obtained, and then the reliability is obtained based onthe color similarity.

FIG. 4 is a view illustrating a method for obtaining a reliability basedon a mixed rate Mix_Rate and a color similarity C_Sim. The reliabilityis represented as follows:

 Reliability=Mix_Rate+(1−Mix_Rate)(C _(—) Sim)  (1)

where Mix_Rate is a value between 0 and 1.

Namely, the value of the mixed rate Mix_Rate becomes 1, the reliabilityof Equation 1 is determined by the Mix_Rate, and as the Mix_Rate becomes0, the reliability of Equation 1 is determined by the color similarityC_Sim. In other words, as the mixed rate of the color in the imageregion is increased, it means that the colors are uniformly distributed,and the color of the region may be visually recognized as one color byhuman eyes. In this case, the reliability of the representative colorvalue is largely affected by the mixed rate Mix_Rate, and as the mixedrate of the colors is decreased, the reliability of the representativecolor value is largely affected by the color similarity C_Sim.

The color similarity C_Sim is obtained by the method as shown in FIG. 3,and as shown in FIG. 5, the mixed rate of the colors Mix_Rate isobtained using a ratio that each color occupies in the image region withrespect to all colors of the image region and an expansion rate whichrepresents that each color is mixed with other colors.

The method for obtaining the mixed rate of the colors will be explainedwith refernece to FIG. 5.

The portion Ci that the pixel having each color Ci occupies in the imagewith respect to all colors in the image is obtained. For example, in thecase of a red color, the portion(Red)=(the total number of pixels of thered color)/(the total number of the pixels in the image). Thereafter,the expansion rate Ci is obtained with respect to each color. Resultsobtained by multiplying two values with respect to all colors in theimage are summed for thereby obtaining the mixed rate Mix_Rate of thecolors as follows:

 Namely, the mixed rate Mix_Rate=

$\sum\limits_{i = 1}^{n}$

 Portion(Ci)×Expansion_Rate(Ci)  (2)

where n represents the total number of colors in the image.

The method for obtaining the expansion rate with respect to each colorin the image region will be explained with refernece to FIGS. 7 and 8.The expansion rate Ci with respect to each color Ci is obtained asfollows.

Expansion_Rate(Ci)=Expansion(Ci)/Max_Expansion(Ci)

where Max_Expansion(Ci) represents the maximum expansion valuedetermined based on an esize and the image region as follows, and theesize represents a value which is in proportion to the size of theexpansion mask.

Max_Expansion(Ci)=ME(Ci); if Me(Ci)<the size of the image region

Max Expansion(Ci)=the size of the image region; if ME(Ci)≧the size ofthe image region.

ME(Ci)=(4esize²+4esize+1)×(the number of the pixels having the color Ciin the image region), where esize=(Width of Expansion_Mask−1)/2, and thewidth(=height) of the Expansion_Mask is an odd number.

The esize is a value proportional to the size of the expansion size anda value for obtaining the degree of the effect that a certain pixelinfluences.

The Expansion(Ci) is obtained by the following sequence.

(a) The esize is determined. Here, the esize is a value proportional tothe size of the Expansion_Mask(701 of FIG. 7, and 801 of FIG. 8) andrepresents a degree of a range that a certain pixel influences.

(b) The number of the pixels having a corresponding color Ci in theimage region is obtained.

(c) The expansion_Mask is overlapped with respect to all pixels in theimage region, and it is searched whether or not corresponding colorexists in the mask, and a mask center cell is a corresponding color asshown in FIGS. 7 and 8. If a corresponding color does not exist in themask, and the mask center cell does not have a corresponding color, theexpansion(Ci) value is increased by +1. For example, in the FIG. 8 inthe case that the expansion is obtained with respect to the colorrepresenting as “C3”, since the center cell of the mask is not the color“C3”, and the color “C3” exists in the remaining mask regions except forthe center cell of the mask, +1 is added to the Expansion(C3) value.

(d) The above-descried operation is performed with respect to all imageregions, and the Expansion(Ci) obtained as a result of theabove-described operation is added to the number of the pixels having acorresponding color for thereby finally setting the Expansion(Ci) value.

FIG. 7 is a view in which the Expansion_Mask 701 having the width andheight of 5 and the esize of 2 is moved at every one pixel 703 in theimage region, and FIG. 8 is a view in which the Expansion_Mask 801 isadapted to one pixel 803 in the image region 802. The numerals indicatedin each pixel represent the color value of each pixel.

When the Expansion_Rate, Mix-Rate, color similarity values are obtained,it is possible to obtain a reliability as shown in FIG. 4.

The method for designating a representative color using the thuslyobtained reliability will be explained with reference to FIG. 9.

The reliability value obtained by the method as shown in FIGS. 2 through8 is compared with a threshold value(hereinafter, called as a thresholdvalue 1). As a result of the comparison, if the reliability value islarger than the threshold value 1, namely, if it is possible to expressthe image region using one representative value, the average of allcolor values of the image region is designated as a representative colorvalue.

However, if the reliability is smaller than the threshold value 1,designating the average color of the image region as a representativecolor of the region is inaccurate, another method is adapted.

In the case that the reliability is smaller than the threshold value 1,a frequency of the pixels in which the chrominance exceeds a certainlevel in the image region is obtained. The method for obtaining thefrequency of the pixels which have a chrominance exceeding a certaindegree is shown in FIG. 6. As shown in FIG. 6, a chrominance element isextracted from each pixel with respect to all pixels in the imageregion, and then the number of the pixels having a chrominance exceedinga certain level is obtained, and the number of the pixels is divided bythe number of the pixels in all image regions for thereby obtaining afrequency(hereinafter called as a chrominance color portion) of thepixels having a chrominance exceeding a certain degree. As a result ofcomparing the chrominance color portion with a certain thresholdvalue(hereinafter called as a threshold value 2), if the chrominancecolor portion is smaller than the threshold value 2, it means that aclear color which represents an image region does not exist. Therefore,the average color of the image region is designated as a representativecolor.

As a result of the comparison, if the chrominance color portion islarger than the threshold value 2, it means that a clear color which isa representative of the image region exists, the representative color isdesignated as follows.

A hue element is extracted from the color of each pixel with respect toall pixels of the image region, and then is quantized for therebyforming a HUE histogram. The HUE histogram is formed by a descendingseries, and then the bin value is summed in the bin sequence having thelarger values. The summing operation is performed until the summed valueexceeds a certain threshold value(hereinafter called as a thresholdvalue 3). When the summed result is larger than the threshold value 3,the color set corresponding to the summed bin is assumed as a HUE_SET,and an average of the pixel values in a corresponding image is obtained.The thusly obtained value is designated as a representative color.

FIG. 10 is a flow chart of a method for designating a representativecolor value using a reliability which is different from the embodimentof FIG. 9. This method will be explained. If the reliability is smallerthan the threshold value 3, a hue histogram is obtained, and theabove-described process is performed with respect to all colors Ci. Thehue(hi) of a certain color Ci is obtained, and the cases that the thuslyobtained hue(hi) is larger is counted, and then the average value C av hof the color Ci is computed. The above-described operation is repeatedlyperformed until the final pixel in the image. When the final pixel iscomputed, in the case that there is not a hue(hi) value which is largerthan a threshold value 4, namely, in the case that the count value is 0,the value obtained by averaging all colors in the image region isdesignated as a representative value. In the case that the count valueis not 0, namely, if there is at least one hue(hi) value larger than thethreshold value 4, the average value of the colors having a hue(hi)value larger than the threshold value 4 is designated as arepresentative color with respect to the region.

FIG. 11 is a view illustrating a representative color expression methodof a grid region formed of 64 local cells which are expressed by areliability with respect to the representative color value in the imageregion. Namely, a color information is expressed based on arepresentative color value Cij and a reliability Sij of the local cell.

FIG. 12 us a view illustrating a sequence for segmenting an image regioninto grids and designating a representative color value with respect toeach local cell. It is possible to implement a reliable image processingby segmenting an image region into local cells and expressing areliability as well as a representative color which is expressed as arepresentative cell with respect to each local cell.

FIG. 13 is a view illustrating an adaptation of the method of FIG. 12and a comparison by segmenting the images G1 and G2 into grids as shownin FIG. 11 and expressing a representative color and reliability withrespect to each local cell when comparing two images G1 and G2 having an×m size.

Namely, the color similarities C_Sim(C1ij, C2ij) and reliability S1ij,S2ij of the local cells corresponding to each local cell of the imagesG1 and G2 are obtained, and the similarities RC_Sim(G1, G2) of two imageregions G1, G2 are determined by multiplying the color similarity andreliability. Here, C1ij represents a representative color value withrespect to the local cell (i,j) of the image G1, and S1ij represents areliability with respect to the representative color of the local cell(i,j). In addition, in the color similarities C_Sim(C1ij,C2ij), thelocal cell(i,j) of the image G1 and the local cell(i,j) of the image G2may be expressed as a distance difference in the color coordinate spacebetween C1ij and C2ij. Any type of color coordinate space may be used.As the color coordinate space is uniformly changed, the value obtainedbased on the color coordinate space becomes accurate.

The similarities RC_Sim(G1, G2) between two image regions G1 and G2having a n×m size may be obtained based on a weight in accordance with areliability value. The following is an example of the above-describedmethod.${{RC}_{-}{{Sim}( {{G1},{G2}} )}} = \{ {\sum\limits_{i = 1}^{n}{\sum\limits_{j = 1}^{m}\lbrack {{{axS1ijxS2ijx}\quad C_{-}{{Sim}( {{C1ij},{C2ij}} )}} + { {{bx}( {1 - ( {{S1ij} - {S2ij}} )} } \rbrack^{2}/\lbrack {({nxm}){x( {a + b} )}} \rbrack}} \}}} $

where a, b represent weights based on a reliability, and it is possibleto obtain a similarity between two image regions by adjusting the valuesa and b.

Next, the method that a color segmentation is performed for segmentingthe region formed of the same colors using the reliability will beexplained.

It is possible to perform a color segmentation using the reliability byrecognizing the case that the value of the reliability exceeds a certainlevel as the same color even when the colors are not the same.

FIG. 15 illustrates the above-descried color segmentation method, andFIG. 14 illustrates a quad tree for dividing the image into four parts.

Namely, the reliability of the image region is obtained, and the imageregion in which the reliability is below a certain thresholdvalue(hereinafter called as a threshold value 5) is segmented into fourparts for thereby obtaining a representative color and reliability.

The reliability of each of divided four region is compared with thethreshold value 5, and the region having a threshold value below 5 issegmented into four parts. The above-described operation repeatedlyperformed until the reliability of all regions exceed 5. Therefore, inthis case, since all segmented regions have a reliability of above 5,the above-descried sub-regions may be recognized as one color.

In other words, the entire images or a certain region designated by auser are expressed by a quad tree method, and each region of the quadtree is expressed as a representative color and reliability. Theabove-described quad tree type region segmentation is repeatedlyperformed until all regions have a threshold value above a certaindegree.

As described above, in the present invention, the representative colorvalue of the image region is expressed together with the reliability, sothat the weight is determined based on the reliability during the imagesearch. When measuring the color similarity between two images, it ispossible to accurately measure the color similarity using thereliability for thereby enhancing an image search performance.

In addition, in the present invention, the representative color valuesof the image region are expressed together with the reliability, so thatit is possible to more effectively perform a color segmentation inaccordance with the degree of the reliability when performing a colorsegmentation in which the image region is segmented into sub-regions forthereby displaying the colors based on the same color.

Although the preferred embodiment of the present invention have beendisclosed for illustrative purposes, those skilled in the art willappreciate that various modifications, additions and substitutions arepossible, without departing from the scope and spirit of the inventionas recited in the accompanying claims.

What is claimed is:
 1. In a method using a color value as informationwith respect to an image region, a representative color designatingmethod, comprising: determining a representative color value thatrepresents the image region; and determining a reliability of therepresentative color value as color information of the image regiontogether with the representative color value that represents the imageregion.
 2. The method of claim 1, wherein said reliability is directedto a degree that one image region is expressed by one color thatrepresents the one image region.
 3. The method of claim 2, wherein saidreliability is determined based on a mixed rate of colors in the imageregion and a color similarity of the image region.
 4. The method ofclaim 3, wherein said method for obtaining the reliability includes: astep for averaging a color value of the image region and removing theelements of the mixed rate; and a step for obtaining a color similarityof the image region and setting the color similarity as a reliability ofthe image region.
 5. The method of claim 3, wherein said method forobtaining a reliability includes: a step for obtaining a mixed rate ofcolors; a step for obtaining a color similarity; and a step for settinga mixed rate of the colors and a reliability value in accordance withthe color similarity.
 6. The method of claim 5, wherein said reliabilityis set based on the following expression: Reliability=mixed rate ofcolors+(1−mixed rate of colors)×color similarity.
 7. The method of claim3, wherein said method for obtaining the color similarity includes: astep for obtaining an average value of the colors of all pixels of animage region; a step for obtaining hue, light, chrominance elements withrespect to the average value; and a step for obtaining hue, light andbrightness elements with respect to each pixel of the image region andusing a result obtained by summing the distance values in the colorcoordinate space of the hue, light and chrominance elements of thepixels and the hue, light and chrominance elements of the average valueas a color similarity.
 8. The method of claim 7, wherein said third stepfurther includes a step in which a result obtained by summing thedistance values in the color coordinate space of the hue, light andchrominance elements of each pixel in the image region and the hue,light and chrominance elements of the average value is normalized, andthen a result obtained by subtracting the normalized from 1 isdetermined as a color similarity.
 9. The method of claim 3, wherein saidmethod for obtaining a mixed rate of the colors of the image regionincludes: a step for obtaining a color portion which is a ratio that thepixels having the colors with respect to a certain color of the imageregion occupy in the image region; a step for obtaining an expansionrate which represents a degree that the colors are mixed with othercolors in the image region; a step for multiplying the color portion andthe expansion rate; and a step for performing the above-described stepswith respect to all colors in the image region, summing for all valuesfrom said performance and determining the obtained values as a mixedrate of the colors.
 10. The method of claim 9, wherein said colorportion of the colors is determined by dividing the number of the pixelshaving a certain color by the total number of the pixels in the imageregion.
 11. The method of claim 9, wherein said method for obtaining anexpansion rate of the colors includes: a first step for obtaining thenumber of pixels having a certain color in an image region; a secondstep for over-lapping the center cells of the expansion mask having acertain size onto one pixel in the image region and checking theoverlapped state, namely, checking whether the center cell of theexpansion mask is not a certain color value but is a certain color inthe region of the expansion mask; a third step for performing the secondstep with respect to all pixels in the image region and summing +1 whenthe overlapped states of the second step are satisfied; a fourth stepfor summing a result of the first step and a result of the third stepand obtaining an expansion result with respect to the color; and a fifthstep for obtaining an esize value set based on the size of the expansionmask and a maximum expansion value which is determined based on thecharacteristic of the image and determining a rate between the expansionvalue and the maximum expansion value as an expansion rate with respectto a certain color.
 12. The method of claim 11, wherein said method forobtaining a maximum expansion value with respect to a certain colorincludes: a first step for obtaining a pixels having a certain colorwhich exists in the size of (expansion mask×expansion mask); a secondstep for comparing a result value of the first step and a size of theimage region; a third step for determining the size of the image regionas a maximum expansion value in the case that the size of the imageregion is larger as a result of the second step; and a fourth step fordetermining a result value of the first step as a maximum expansionvalue with respect to the color in the case that the result value islarger as a result of the comparison of the second step.
 13. The methodof claim 12, wherein said expansion mask is a square shape formed of anodd number of pixels, and the value of the esize is set based on (widthof expansion mask−1)/2.
 14. The method of claim 3, wherein saidrepresentative color value of the image region is determined based on aresult obtained by comparing the reliability with a first thresholdvalue.
 15. The method of claim 14, wherein a representative color of theimage region is determined as an average value of all color values inthe image region in the case that the reliability is larger than thefirst threshold value as a result of the comparison.
 16. The method ofclaim 14, wherein said method for designating a representative color ofthe image region in the case that the reliability is smaller than thefirst threshold value as a result of the comparison includes: a firststep for obtaining a portion of the pixels in which the chrominanceexceeds a certain degree in the image region; a second step forextracting a hue element from the color of the pixel with respect to allpixels in the image region in the case that a result of the first stepis larger than a second threshold value and forming a hue histogram; athird step for summing the hue histogram in a bin sequence of the largervalue and summing until a result of the summing operation exceeds athird threshold value; and a fourth step for designating an average ofthe color set having above the third threshold value as a representativecolor as a result of the summing operation of the fourth step.
 17. Themethod of claim 3, wherein the mixed rate is a degree to which multiplecolors in the image region appear to a viewer as a single colordepending on color distribution in the image region.
 18. In a method forusing a color value as an information with respect to an image region, alocal representative color designation method, comprising: segmenting animage region into n×m local regions; and expressing a reliability of arepresentative color as a color information of each segmented localregion together with the representative color which represents said eachsegmented local region.
 19. In a method for comparing similarities ofimages, a similarity measuring method of an image using a reliability,comprising: segmenting first and second images into corresponding imageregions; expressing a reliability of a representative color value as aninformation of each image region together with a representative colorwhich represents an image region; comparing the reliability of thecorresponding image regions of the first and second images; and judgingthe similarities of the images in accordance with the reliability. 20.The method of claim 19, wherein when measuring a similarity of theimage, the reliability is used as a weight.
 21. A color segmentationmethod for segmenting an image into regions having the same color,comprising: a first step for expressing a reliability of arepresentative color as a color information of a corresponding imageregion together with a representative color which represents an image; asecond step for comparing a reliability of the image region with athreshold value and segmenting a corresponding image region when aresult of the comparison is below the threshold value; and a third stepfor repeatedly performing the second step until the reliability of allsegmented regions exceed the threshold value.
 22. The method of claim21, wherein said image region is expressed using a quad tree, and eachnode of the quad tree represents a segmented region, and said region isexpressed by a representative color and reliability value, and each nodeis segmented until the reliability value exceeds the threshold value.